1. Field of the Invention
The present invention relates generally to a method and apparatus for detecting and tracking a moving object in an image in a portable terminal
2. Description of the Related Art
For many applications such as computer vision and object recognition, robotics, surveillance systems, unmanned vehicle systems, and the like, much study has been conducted on a technology of automatically detecting and tracking a moving object in continuous images acquired from a camera. The technology of detecting and tracking a moving object in images is typically classified into a scheme using template matching, and a scheme of detecting and tracking a moving object in images corrected by correcting for motion of a camera. The template matching-based scheme manually selects, i.e., allows a user to directly select, an object to be tracked in a frame received through a camera, sets some selected areas as templates, tracks an area having the highest similarity in the next frame by template matching, and determines the highest-similarity area as an area of a moving object.
The scheme of detecting and tracking a moving object in images corrected by correcting for motion of a camera, divides a frame received through the camera into several blocks, extracts feature information from each block, estimates a local motion using the extracted feature information, removes an outlier increasing motion estimation error to estimate a global motion based on the estimated local motion information, and estimates the global motion using the outlier-removed feature information. The scheme then calculates different motion information of a moving object and a background in continuous images, in which the motion of the camera is corrected, using features of the images, and separates the moving object from the background.
However, these moving object detecting and tracking schemes have several problems. The scheme of manually selecting an area of an object and tracking the area of the object by determining its similarity based on template matching is inconvenient and may continue to track a part of a non-moving object if it fails in template matching. Additionally, if a moving object is out of a preview area of the camera, this scheme cannot track the moving object and must newly select the moving object. Moreover, if a size of the selected moving object is large, the computing speed is low during template matching, leading to a delay of a preview frame being input to the camera.
Next, the scheme of correcting motion of a camera by estimating a local motion and a global motion and then detecting a moving object using features of images, generally uses a method of estimating motion based on features of images, considering the speed, and the features of images refer to edges of objects, boundaries of areas, intersections of lines, etc. To extract feature information, a Harris corner detection method or a Kansde-Lucas-Tomasi (KLT) edge detection method is commonly used, and the edge detection method may be classified into Sobel, Canny and Laplace edge detection schemes. It may not be possible for these various feature information extraction methods to be carried out in real-time in electronic devices having limited storage capacity and arithmetic processing capability, like cell phones. In some cases, considering the speed, input images should be down-sampled to a low resolution during their processing. In this case, however, the processing speed may increase, but the performance of motion estimation may decrease.
Thus, a moving object detecting and tracking method suitable for the arithmetic processing capabilities of portable terminals is required.